app.py

import streamlit as st
from transformers import pipeline

# Create a text generation pipeline
pipe = pipeline("text-generation", model="ismaelfaro/gpt2-poems.en")

# Define the Streamlit app
st.title("Text Generation with Hugging Face Transformers")

# Input for user to provide a seed text
seed_text = st.text_input("Enter a seed text:")

# Button to generate text
if st.button("Generate Text"):
    if seed_text:
        generated_text = pipe(seed_text, max_length=50, do_sample=True)[0]['generated_text']
        st.write("Generated Text:")
        st.write(generated_text)
    else:
        st.write("Please enter a seed text to generate text.")

# Instructions and information
st.markdown("This app uses the Hugging Face Transformers library for text generation.")
st.markdown("Model: ismaelfaro/gpt2-poems.en")

# Provide additional information or options here